Prospective Comparison Between Shotgun Metagenomics and Sanger Sequencing of the 16S rRNA Gene for the Etiological Diagnosis of Infections

• Published in: Frontiers in microbiology Vol. 13
• Main Authors: Lamoureux, Claudie, Surgers, Laure, Fihman, Vincent, Gricourt, Guillaume, Demontant, Vanessa, Trawinski, Elisabeth, N’debi, Melissa, Gomart, Camille, Royer, Guilhem, Launay, Nathalie, Le Glaunec, Jeanne-Marie, Wemmert, Charlotte, La Martire, Giulia, Rossi, Geoffrey, Lepeule, Raphaël, Pawlotsky, Jean-Michel, Rodriguez, Christophe, Woerther, Paul-Louis
• Format: Journal Article
• Language: English
• Published: Frontiers Media 06-04-2022
• Subjects: Life Sciences
• ISSN: 1664-302X; 1664-302X
• DOI: 10.3389/fmicb.2022.761873

Bacteriological diagnosis is traditionally based on culture. However, this method may be limited by the difficulty of cultivating certain species or by prior exposure to antibiotics, which justifies the resort to molecular methods, such as Sanger sequencing of the 16S rRNA gene (Sanger 16S). Recently, shotgun metagenomics (SMg) has emerged as a powerful tool to identify a wide range of pathogenic microorganisms in numerous clinical contexts. In this study, we compared the performance of SMg to Sanger 16S for bacterial detection and identification. All patients’ samples for which Sanger 16S was requested between November 2019 and April 2020 in our institution were prospectively included. The corresponding samples were tested with a commercial 16S semi-automated method and a semi-quantitative pan-microorganism DNA- and RNA-based SMg method. Sixty-seven samples from 64 patients were analyzed. Overall, SMg was able to identify a bacterial etiology in 46.3% of cases (31/67) vs. 38.8% (26/67) with Sanger 16S. This difference reached significance when only the results obtained at the species level were compared (28/67 vs. 13/67). This study provides one of the first evidence of a significantly better performance of SMg than Sanger 16S for bacterial detection at the species level in patients with infectious diseases for whom culture-based methods have failed. This technology has the potential to replace Sanger 16S in routine practice for infectious disease diagnosis.